563 results about "Information needs" patented technology

The invention discloses a method for generating and constructing a database test knowledge base based on an open source large language model and retrieval enhancement, and relates to the technical field of database testing, and the method comprises the steps: building a local deployment system on a local computer system or server, and achieving the efficient local operation of the open source large language model and the stable output of language processing service; on a local computer system or a server, a retrieval enhancement generation framework is constructed, and accurate knowledge support and reliable content output are provided for local language processing service by integrating multi-modal knowledge, optimizing retrieval and generation processes and guaranteeing safety and compliance; on a local computer system or a server, a personalized database knowledge base is built, database related information is collected and processed from multiple channels and is output in an adaptive form, and the specified information requirement of local personalized language processing service is met. According to the method, efficient and stable operation of the open source large language model is realized, accurate and reliable language processing output is realized, and personalized services meet specific requirements.

The invention discloses a key intelligence demand intention understanding method based on a large model. The method comprises the following steps: constructing a key intelligence demand intention understanding large model; the large model comprises an interaction instruction understanding algorithm, a combat scheme understanding algorithm, a context prompt learning technology, a heterogeneous intelligence association fusion algorithm and a multi-modal intelligence understanding algorithm; establishing automatic intelligence analysis and understanding by combining large-model efficient parameter fine tuning, retrieval enhancement generation and cue word technology; intention understanding is carried out on key intelligence demands based on a large model; the decision-making module is used for decision-making based on intelligence, and the decision-making based on intelligence comprises associated commander key information demand generation, task decision point mining and appointed traction branches and subsequent plans. The invention further discloses a system, electronic equipment and a computer readable storage medium, based on a military big language model, efficient parameter fine tuning is utilized by the big model, an iterative intelligence vector database and a flexible intelligence task cue word template are implemented, and the intelligent processing capacity of intelligence data is remarkably improved.

The invention relates to a knowledge base question answering method and device and a computer readable storage medium, and belongs to the technical field of artificial intelligence. A query question input by a user is received; the query problem is analyzed, and keywords in the query problem are extracted; retrieving slice data matched with the query problem from a retrieval enhancement generation system on the basis of the text correlation between the keyword and the slice data; wherein a plurality of slice data are pre-stored in the retrieval enhancement generation system, the slice data comprise text slices and image-text slices, and the image-text slices comprise storage paths of images and image descriptions with text context information of the images; and inputting the retrieved slice data into a multi-modal large model, generating an answer related to the query question and an image matched with the answer, and outputting the question answer with the image. According to the method, the capability of an original retrieval enhancement generation system is remarkably improved, and the information requirement of a user in an image-text environment is more comprehensively met.

The invention relates to the technical field of artificial intelligence, in particular to an agent dynamic decision network generation method based on reinforcement learning. The method comprises the following steps: receiving information demand data input by a user; performing feature analysis on the information demand data, and extracting a business target, a constraint condition and a key parameter to obtain an information demand analysis result; identifying a task flow corresponding to the information demand analysis result, and matching an API call chain according to the task flow to obtain a task demand technology blueprint; generating an agent workflow according to the task demand technology blueprint by using a preset dynamic workflow engine; performing context analysis on the language demand analysis result to obtain context information; the agent workflow is divided into ultra-long thinking chains based on context information. In conclusion, through the reinforcement learning technology, the intelligent agent can be automatically generated and continuously optimized according to user requirements, and efficient decision making and dynamic adaptation of complex service scenes are supported.

The invention discloses a multi-agent dynamic arrangement method based on multi-modal analysis and adaptive retrieval, and relates to the technical field of artificial intelligence and information retrieval. Comprising the steps of S1, converting a text, an image, structured data and voice content input by a user into a unified multi-mode semantic representation, S2, converting the unified multi-mode semantic representation into a specific execution process, and S3, automatically scheduling a reasoning agent, a knowledge obtaining agent and an execution agent according to DAG nodes, task elements and available resources, and obtaining the task elements and the execution agent according to the reasoning agent, the knowledge obtaining agent and the execution agent. S4, after task process construction and agent arrangement are completed, dynamic retrieval, evidence convergence and strategy optimization are carried out on information requirements related to a user task, so that a reasoning agent obtains complete knowledge support with consistent context, and S5, knowledge evidence is combined with a task process, so that the task process is completed. The method comprises the following steps: step S6, implementing problem solving, strategy generation and task closed-loop execution through a reasoning agent, step S6, performing actual operation on a target task by an execution agent according to an executable instruction sequence output by the reasoning agent, and outputting a result, and step S7, performing result verification according to an output result returned by the execution agent, and the correctness, integrity and consistency of an output result are examined through rule verification, model evaluation and evidence alignment.

The invention discloses an information extraction method and device based on a large language model, equipment and a storage medium, and relates to the technical field of information extraction, and the method comprises the following steps: converting an original text into a to-be-extracted character string; extracting entities and relationships from the to-be-extracted character string according to the pre-labeled sample; retrieving from a professional knowledge database according to the original text, the entity and the relationship to obtain a related professional knowledge text; according to the original text, the entity, the relationship and the related professional knowledge text, constructing cue words; and inputting the original text, the entity, the relationship and the cue word into a large language model, so that the large language model outputs extraction information of the original text. According to the method, entities and relationships can be accurately extracted from character strings by using a small amount of annotation data through pre-annotation samples, the extracted entities and relationships are retrieved in a professional knowledge database according to an original text, and cue words are generated in combination with retrieval contents, so that a large language model is helped to understand information needing to be extracted, and the extraction efficiency is improved. And then proper information is extracted.

The invention belongs to the technical field of artificial intelligence and multi-modal large model reasoning enhancement, and discloses a multi-modal retrieval enhancement generation method based on gradual group relative strategy optimization. A step-by-step reasoning track construction mechanism is introduced, an original problem is disassembled into a plurality of sub-problems, and in each step, a new retrieval query is autonomously generated in combination with reasoning history and current information requirements, and a most appropriate knowledge source is selected for evidence retrieval; and in the reasoning process, each step of decision and answer obtains a fine-grained reward signal. According to the method, a group relative strategy optimization method is adopted, the query quality of each reasoning step, the knowledge base routing accuracy, the answer content format compliance and the final answer accuracy are used as step-by-step rewards for joint modeling, and model parameters are optimized through global and local multiple feedback signals. The method is remarkably superior to the existing similar technology in tasks such as multi-class multi-modal open domain question answering and complex reasoning, and has excellent answer accuracy, retrieval efficiency and multi-modal adaptive capacity.

The invention discloses an intelligent question answering system and method based on question decomposition and community semantic search. According to the method, firstly, a complex question is decomposed into a plurality of single-hop sub-questions through an original loop question decomposition technology, then information needed for answering each sub-question is obtained based on communities in a vector retrieval knowledge graph, and the sub-questions are answered by using a large language model. And finally, generating a final question and answer for the original complex question by combining the LLM with the answers of all the sub-questions. Compared with other methods in the industry, the method has the advantages that the information integration capability is remarkably improved, information fragmentation is avoided through community-level search and abstract generation, and high-quality and logically consistent answers are provided. When a complex query is processed, the effect of the method is superior to that of a general method in the industry and is improved by 29% at most; meanwhile, on the basis of ensuring a better question and answer effect, the efficiency is remarkably improved, and on the premise that the effect exceeds that of an existing optimal method GraphRAG, the token consumption is only 3.2% of that of the existing optimal method GraphRAG.

A computing system for progressive virtual assistance in tax applications includes a computing device with processing circuitry configured to implement a tax application virtual assistant program. The processing circuitry is configured to receive a tax-related user query, identify an intent in the query, and select a workflow including operations required for responding to the intent. The processing circuitry is further configured to implement a workflow orchestrator to schedule a sequence of the operations, identify information needed to complete a target operation, and generate and input an information augmentation prompt to a large language model to retrieve the information. The processing circuitry is further configured to receive a response to the information augmentation prompt, generate and input a user query response prompt to the large language model, receive the user query response, and display the user query response in a chat interface.

The invention provides a digital human video generation method and device based on a large model, an intelligent agent, electronic equipment and a storage medium, relates to the technical field of artificial intelligence, in particular to the technical fields of deep learning, the large model, computer vision and the like, and can be applied to scenes such as video live broadcast, advertisement production, e-commerce sales and the like. The digital human video generation method based on the large model comprises the steps that demand information is acquired, the demand information comprises action description information used for describing a specified action video clip, and the action video clip represents a specified action of a target object; processing the demand information by utilizing a language large model to obtain a target script which comprises a target oral playing fragment text matched with the action description information; and processing the target script and the action video clip by using a visual large model to obtain a target video which is used for displaying oral playing of the target object based on the target oral playing clip text in the process of executing the specified action.

The invention relates to the technical field of information processing, and discloses a big data-based information matching management system, which comprises an acquisition module, an attribute analysis module, a multi-dimensional modeling module and a dynamic matching module. The acquisition module acquires a user behavior data set and extracts active information demand features; the attribute analysis module analyzes the real-time updating frequency, the semantic association degree, the historical matching success rate and the data topological structure characteristics of the target information resources; a multi-dimensional modeling module performs heterogeneous modeling on each feature to generate timeliness, semantic association, matching probability feature vectors and topological structure vectors; and the dynamic matching module generates an adaptation degree score and determines an optimal matching object through heterogeneous space projection and feature coupling operation. The system improves the accuracy, real-time performance and efficiency of information matching through multi-dimensional feature processing, topological structure analysis and a dynamic matching algorithm, and is suitable for an accurate information matching scene in a big data environment.

The invention discloses a medical text data synthesis method based on role driving, and relates to the technical field of text data synthesis and artificial intelligence, and the method comprises the following steps: S100, generating an original problem; s200, screening original problems; and S300, synthesizing the medical text data. According to role description and interest content generation, the adaptability to different medical role requirements is enhanced, semantic duplicate removal and correlation evaluation are realized by utilizing a text coding model and a vector database, semantic duplicate content is removed, correlation is accurately evaluated by utilizing a large language model, the data quality and diversity are improved, and the method is suitable for popularization and application. Through generation of variant questions and answers, diversity and practicability of medical text data are enriched. According to the method, the personalization and pertinence of the medical text data are improved, the quality and duplicate removal efficiency of the medical text data are enhanced, the problem types are enriched, the generated content is optimized, and various information requirements of the medical text data are comprehensively covered.

The invention relates to the technical field of information pushing, in particular to a platform user interest recommendation method and system based on artificial intelligence. The method comprises the following steps: acquiring user action data and environment perception data, analyzing the user action data and the environment perception data, and constructing a unified space-time semantic network; according to the unified space-time semantic network, analyzing scene features of the user, and determining a multi-dimensional dynamic scene feature set; and analyzing the multi-dimensional dynamic scene feature set, determining composite scene demand information of the current user, and retrieving and pushing real-time demand information of the user according to the composite scene demand information. According to the method and the device, the perception capability of the pushed information to the user demand scene is improved, the multi-dimensional dynamic adaptation of the pushed information to the platform user is realized, the information pushing accuracy for the platform user is improved, and the composite information demand of the user in a complex scene is met.

The embodiment of the invention provides a method, device and system for constructing an attack graph, and a storage medium, and relates to the technical field of network security. The method comprises the steps that based on a test case knowledge base of a target system, an attack graph information expansion algorithm is executed through a knowledge graph technology, and expanded information is obtained; utilizing the expanded information to construct an attribute attack graph of the target system; and carrying out attack path description on vulnerabilities of the target system based on the attribute attack graph. An attack graph information expansion algorithm is executed through a test case knowledge base based on a target system and by means of a knowledge graph technology, information needed for constructing an attack graph can be obtained, potential attack paths can be mined, the attack graph information is expanded, and then a comprehensive and accurate attribute attack graph is constructed. According to the method, effective description of the vulnerability attack path of the target system is realized, so that the constructed attack graph can reflect the security condition of the network system more truly, more scientific decision support is provided for network security management personnel, and the network security protection effect is improved.

The invention discloses an end-to-end automatic driving decision planning model and device combining a vectorized map and multi-task feature embedding. The end-to-end automatic driving decision planning model comprises six task branches of different modules such as perception, decision and control. An end-to-end automatic driving framework is utilized to reduce errors between different model transmissions, and a multi-task constraint mode is utilized to improve the fitting ability of the model. Vectorized map and aerial view target detection are combined to serve as perception representation of a multi-task model, dynamic and static target information needed in aerial view space is provided, environment perception information and decision navigation point output are unified to the same space, and model prediction precision is improved. Information transmission is performed by using a cross attention mechanism between different tasks, training conflicts caused by simple sharing of feature maps in a traditional multi-task model are overcome, efficient coupling between different tasks is realized, and model prediction precision is improved.

The invention relates to a server test environment automatic monitoring method and system. The method comprises the following steps: acquiring various data in a test environment of a plurality of servers in a specified period, and dividing the data into a training set, a test set and a verification set; the method comprises the following steps of: acquiring various monitored server test environments, inputting the monitored server test environments into a server test environment monitoring model for training, testing and verifying, acquiring various data in the monitored server test environments in real time, inputting the data into the server test environment monitoring model, and outputting monitoring results of the monitored server test environments in real time through the server test environment monitoring model. And the server obtains abnormal information according to the monitoring result, obtains an abnormal position and an abnormal severity degree of the monitoring test environment based on the abnormal information according to whether the abnormal information needs to be processed or not, analyzes an abnormal solution according to the abnormal position and abnormal data, and processes the abnormality based on the obtained abnormal solution. The server test environment monitoring efficiency is effectively improved, and the missed test rate is reduced.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.

The embodiment of the invention provides an information acquisition method and device and electronic equipment, and relates to the technical field of computers. The information acquisition method comprises the following steps: acquiring a webpage address of a first webpage; collecting first original webpage information corresponding to the webpage address of the first webpage; according to an information extraction rule, first webpage information is extracted from the first original webpage information, the information extraction rule is data generated through a large language model according to content description information and second original webpage information of a second webpage, and the content description information indicates webpage information needing to be obtained from the webpage. According to the method and the device, the adaptability to variable webpage structures can be improved, and the webpage information extraction efficiency is improved.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.

The invention provides an outline content generation method and system combined with natural language processing, and the method comprises the steps: firstly carrying out the medical semantic analysis of a medical question text inputted by a user, obtaining a question feature set, calling a medical literature database interface for retrieval based on the question feature set, and obtaining a matched medical literature knowledge set; extracting medical knowledge units with independent semantics from the literature knowledge set to generate a structured knowledge unit set, performing association matching on the structured knowledge unit set and the question feature set, distributing weights according to question type identifiers and information demand strength parameters to generate a weighted knowledge integration result, and performing knowledge integration on the weighted knowledge integration result; and finally, generating a medical question answering text according to a weighted knowledge integration result, and feeding back the medical question answering text to a user interaction interface for display, so that accurate, comprehensive and personalized medical question answering can be provided for the user, and the question answering quality and the user experience of a medical academic community are improved.

The invention discloses an active power distribution network route scheduling and dynamic selection method and system driven by business requirements, and belongs to the technical field of active power distribution network control. The method comprises the following steps of: evaluating a physical importance index and an information importance index of each piece of service flow according to physical influence and information requirements of issuing each piece of service flow, comprehensively considering the physical importance index and the information importance index to obtain a comprehensive importance index, and sorting to obtain a sorted service flow set; quantizing the real-time performance and reliability of a routing link, and generating a routing distance matrix; inputting the sorted service traffic set and the routing distance matrix into a routing scheduling optimization model, and generating a routing scheduling scheme of the overall service traffic based on the service traffic importance and routing path performance matching principle; according to the method, the physical traffic importance index and the information importance index are comprehensively considered, the comprehensive importance index is obtained, and the problem that service traffic evaluation is not comprehensive in an information physical coupling scene is solved.

The invention discloses an automatic driving high-risk fuzzy test scene generation method, and the method comprises the steps: carrying out the deconstruction of a scene according to the construction demands of an automatic driving test scene, and extracting the static environment information needed by the test scene and the dynamic parameter distribution of traffic participants; static environment information and dynamic parameters of traffic participants are sampled, and a scene is extracted into a plurality of scene sections; scene section generalization generation is realized by using a conditional table adversarial generative network; through each generated scene section, according to scene variable parameter distribution, behavior uncertainty is captured by using a triangular fuzzy number, and a complete fuzzy track sequence is expanded; constructing an automatic driving high-risk fuzzy test scene in combination with the static environment information and the fuzzy trajectory sequence; therefore, not only is the coverage rate of the test scene improved, but also the pertinence and authenticity of the test are enhanced, and more effective support is provided for safety performance evaluation of the automatic driving system in a complex environment.

The invention provides a scientific and technical literature question and answer method and system based on self-feedback iterative optimization, and the method comprises the steps: receiving a user question, and generating an initial response through employing a retrieval enhancement generation strategy; taking the initial response as iterative input, and performing multi-dimensional evaluation on the iterative input to obtain structured feedback with a plurality of specific feedbacks; extracting an information demand from the structured feedback, and performing supplementary retrieval according to the information demand to obtain supplementary information; performing progressive information fusion on the supplementary information and the iterative input according to the priority ranking of the specific feedback to obtain an optimized content; verifying and correcting references in the optimized contents to obtain iterative output; and judging whether an iteration termination condition is met or not according to the iteration output, if so, taking the iteration output as a final response, and otherwise, taking the iteration output input as the iteration input to carry out iteration optimization until the final response is obtained. According to the invention, the answering quality of academic answers can be greatly improved.

The invention relates to the technical field of medical information, and discloses a multi-modal information integration and rebroadcasting meta-universe medical digital space construction method, which comprises the following steps of S1, determining specific requirements and targets of medical application, including data integration and rebroadcasting requirements of an operating room, an I CU, a ward and the like; s2, making a digital transformation plan, and determining the type of multi-modal information needing to be integrated; real-time acquisition and processing of multi-modal information are realized by defining medical requirements, formulating a digital transformation plan and installing equipment and sensors with high compatibility, and data from different equipment and sensors are seamlessly integrated into a unified platform by using a standardized data format and a communication protocol, so that the consistency and the real-time performance of the data are ensured, and meanwhile, the real-time performance of the system is improved. And through Fourier transform and other data processing algorithms, key features are extracted for data cleaning, so that the efficiency and accuracy of data processing are improved, and the integration and processing efficiency of medical data is improved.

The embodiment of the invention provides an information processing method and device, a storage medium and a program product. In the embodiment of the invention, after the intelligent customer service enters the trusteeship state, the question information and the subsequent question information received within the validity period of the distributed lock are stored in the message queue as a current batch of question information needing delay processing, the delay processing can give real communication feeling to merchants, and the service experience of the merchants is improved. Furthermore, under the condition that timing of the timing task of the message queue is finished, an AI question and answer service model based on artificial intelligence is called to perform unified reply processing on the question information currently needing delay processing in the message queue, so that target reply information corresponding to the obtained question information is sent to a client of a target merchant; and the target merchant can check the target reply information corresponding to each piece of question information, so that manual customer service is replaced, the labor is saved, and the question processing efficiency is improved.

The invention discloses a traffic knowledge graph automatic generation system and method, relates to the technical field of traffic informatization and smart travel, and aims to solve the problem that an existing traffic information management system is difficult to effectively classify and integrate multi-source heterogeneous data. The system comprises a collection device used for collecting multi-source heterogeneous data in the traffic field and sending the multi-source heterogeneous data to a traffic knowledge graph generation module; the traffic knowledge graph generation module is used for generating and managing a traffic knowledge graph based on the multi-source heterogeneous data and sending the traffic knowledge graph to the server for storage; and the terminal equipment is used for sending an interaction instruction to the traffic knowledge graph generation module and receiving target information generated by the traffic knowledge graph generation module based on the interaction instruction. The traffic knowledge graph automatic generation system provided by the invention is used for carrying out efficient integration and classification on multi-source heterogeneous data so as to meet information requirements of different scenes in a complex traffic environment.

The invention relates to the technical field of research and development management and the field of financial science and technology, and discloses an editor and language service separation analysis method, which comprises the following steps of: defining a communication protocol between an editor and a language server, monitoring file processing operation in the editor, generating a standard behavior event, and analyzing the standard behavior event. Sending the standard behavior event to a language server through an editor, analyzing the event by the language server, determining a corresponding file processing operation type, executing a language service based on the operation type, generating a service result, and judging whether feedback information needs to be sent to the editor or not; if it is determined that feedback is needed, language service feedback data are generated, the feedback data are sent to the editor through a communication protocol, and the editor updates editing feedback information displayed in the interface based on the feedback data. According to the invention, by breaking the tight coupling between the editor and the language server, the complexity of independently developing the language server for each language in different editors is avoided, and the development cost is reduced.

A system and method for an AI-based Automated Software Application Development Platform which intelligently gathers requirements from a business analyst and generates a runnable software application from those requirements. The AI-based platform enables the business analyst with no technical knowledge to visually model their requirements rapidly without requiring any programming Using the abstract requirements architecture and the platform, the analyst creates requirements models for the application's business processes and business tasks for each of the processes, including defining the supporting information needs. The system intelligently assists the user in defining the information needs for each of the business processes and their tasks. Once the requirements models are created by the analyst with the help of the platform, the platform automatically designs and creates an appropriate persistent canonical data model for the application from the defined information needs. The platform then creates a runnable software application. The system also provides a template for the user to input their requirements in descriptive text, and accepts requirements document for applications as written free form text or text documents written in English as input, and in a non-English language that the system automatically translates them into English. The system provides a method for reverse engineering an existing application, including generating a requirements document for the existing application such as a legacy modernization or digital transformation an old applications for redesigning, updating or revising them to accommodate a new requirements set for such applications.

The embodiment of the invention provides a memory information processing method of a large language model and a computer program product, and relates to the technical field of large language models. The method comprises the steps of obtaining interaction request information of a target object, extracting at least one piece of memory information needing to be memorized from the interaction request information based on a large language model, performing classification and importance evaluation on each piece of memory information to obtain category information and an importance score of each piece of memory information, and according to each piece of category information, determining the importance score of each piece of memory information. And determining the expiration duration of each piece of memory information, and storing each piece of memory information, the corresponding category information, the corresponding expiration duration and the corresponding importance score into an active memory pool of the target object. Context management can be carried out by using the memory information, and the context management accuracy of a large language model in a cross-session scene is remarkably improved.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.